Alex Rohrbach, Sri Rao
Robots create value through increased productivity, improved quality, mitigated risk, and better decision-making.
This is meant to be a mutually exclusive, collectively exhaustive (MECE) framework characterizing the value created by robots.
Note how this framework implies robots can lead to cost savings and revenue opportunities. The latter is important.
Revenue upside can win over customers and investors. When relevant, these benefits should be highlighted in customer sales and pitch decks.
Let’s look at each bucket in more detail:
1. Robots replace or reduce reliance on human labor → Productivity Increase
Robots leading to productivity increases are an obvious but difficult to measure benefit. We recommend running a life cycle cost (LCC) analysis and comparing it to an appropriate baseline.
The LCC estimates the total cost of an asset including fixed and variable costs and residual value. The baseline is the all-in cost of the activity being automated. The baseline can be the status quo or an alternative solution being considered.
Be precise in defining your baseline. If a robotic cleaning service has similar transportation costs as a human cleaning service baseline, transportation costs should be included or excluded in both.
A few assumptions to consider:
- Installation costs: Assume 3x the price of the machine (unless you have better information)
- Labor costs: Assume 25% of current labor costs remain after launching a robot fleet and be sure to use local salaries (again, unless you have better information)
- Don’t forget to factor in downtime and maintenance for robots
- Consider whether you will see a reduction in scrap and human error (e.g., % reduction in scrap material, fewer reworks).
We can increase productivity value by offering fast installation; shortening downtime for maintenance; creating longer-lasting machines; and selling robots in high labor cost geographies/industries, where the baseline cost may be higher. Each of these components can impact your model.
An example of a robot that unlocks productivity is Cafe X, the robotic coffee bar. Based on their website, the machine costs $225,000 and Cafe X will offer installation support, training, ongoing remote technical support, spare parts, and menu setup support. Once the robotic coffee bar begins operating, Cafe X charges a monthly operational support fee to provide remote support and on-site support as needed. As a baseline, we could compare Cafe X to a cafe kiosk but would need to factor in training, support, and repairs, as these are included with Cafe X. If our theoretical baseline cafe faced a labor constraint, the robotic cafe would enable increased productivity.
Lastly, fleet size can matter for productivity (see diagram below). Assuming no gains from fleet connectivity (our fourth value driver), robots can add incremental value over the efficiency of humans. For small-size fleets, fixed development costs and maintenance may reduce productivity gains. However, as the fleet grows in size, fixed costs and learnings can lead to economies of scale that exceed the baseline.
2. Robots Surpass human capability → Quality Improvement
In some circumstances, robots can work more consistently, reliably, and/or accurately, leading to better quality output. The consequence of improved quality can be increased revenue by offering a superior product or reduced costs (less rework).
For example, Hudson Robotics’ Protean Workcell helps to minimize human error in laboratories. The Workcell is designed to minimize the amount of time human hands can manipulate samples, thereby reducing imposed error and contamination and increasing statistical reproducibility.
Another example is imagers used for quality assurance of package labels (e.g., QX Hawk Imager). These imagers identify wrong labels on food packaging and ensure that all products within one sales batch are the same. By automatically stopping the production line when errors are detected, the imager removes human error and ensures reliable results.
3. Robots reduce danger to humans → Risk Mitigation
Robots reduce danger to humans by working in extreme or inhospitable environments.
In the construction industry, robots remove operators from dangerous environments (less physical risk), lift heavy objects (less risk from falling objects), conduct repetitive tasks (less muscle strain), and work without fatigue (less likely to make mistakes)
An analysis report compiled by OSHA lists 88 window cleaning accidents over a 15-year period, 62 of which resulted in fatalities. Skyline Robotics is building the “future of window cleaning,” with a fleet of window cleaning robots equipped with lidar sensors, controlled by human operators. These robot/human teams can supposedly clean 3x faster than human fleets (productivity improvement), and allow safe operation from a distance.
4. Robots connect and digitize systems → Better Decision Making
The convergence of the Internet of Things and Robotics has led to the term Internet of Robotic Things (IORT).
ABi research appears to have coined this term in 2014, describing IORT as an environment where “intelligent devices can monitor events, fuse sensor data from a variety of sources, use local and distributed ‘intelligence’ to determine a best course of action, and then act to control or manipulate objects in the physical world, and in some cases while physically moving through that world.”
Robot fleets have the potential to drive better decisions relative to humans due to their fundamental nature:
- Ability to respond to environment- While human teams face are likely to be bogged down by slow communication and coordination challenges, integrated robotic systems can collect, share, and act off environmental information.
- Ability to learn- In contrast to human teams that require training to institute new policies (training that employees may or may not complete), integrated robotic systems can fix errors with system-wide updates and ensure compliance.
Amazon uses IORT across its fulfillment centers and even offers “AWS IoT RoboRunner” to provide infrastructure for integrating robots with work management systems and building robotics fleet management applications.
<< Chapter II: A Checklist Definition for Robotics
Chapter IV: Applications of our Value Creation Framework >>
